Agent skill

SEO Keyword Insights

by sandbaseai in sandbaseai/sandbase-skills

Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities.

Apache-2.0Auto-check passedFrontend & Design

Install SEO Keyword Insights

skills CLI
$ npx skills add sandbaseai/sandbase-skills --skill seo-keyword-insights -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sandbaseai/sandbase-skills seo-keyword-insights --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/marketing/seo-keyword-insights .claude/skills/seo-keyword-insights && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-keyword-insights
GitHub stars
203
Token cost
~2.6k tokens
SKILL.md length
1,318 words
Files
4 (incl. references)
Skills in repo
23
Repo updated
First seen
Licence
Apache-2.0

At a glance

Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities.

  • Works in 5 steps: Frame the decision → Select and call SandBase capabilities → Build and validate the keyword universe → …
  • Asked to discover
  • SKILL.md covers Operating principles, Workflow, Example tasks and Quality gate, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Keyword Insights is an agent skill from sandbaseai/sandbase-skills. Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities. Use when asked to discover or prioritize keywords, assess search demand or ranking feasibility, map intent and topics, find competitor gaps, plan organic-search landing pages or content, or analyze a website's SEO opportunities.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/example-workflows.md`, `references/report-template.md` and `references/sandbase-api-map.md`).

It sits in Frontend & Design, covering Landing pages. The repository describes itself as: 88 installable open-source Agent Skills for research, social intelligence, marketing, and business workflows—compatible with Codex, Claude Code, Cursor, Gemini CLI, and DeepSeek… The licence is Apache-2.0.

When your agent uses it

  • Asked to discover
  • Prioritize keywords
  • Assess search demand
  • Ranking feasibility

Example prompts

  • “/seo-keyword-insights”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Frame the decision
  2. Select and call SandBase capabilities
  3. Build and validate the keyword universe
  4. Interpret intent, competition, and opportunity
  5. Produce an execution plan

What it can do on your machine

Read from SKILL.md and the folder at commit cbab581. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Keyword Insights loads about 2.6k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 96 tokens; SKILL.md has 1,318 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sandbaseai/sandbase-skills at commit cbab581, republished under its Apache-2.0 licence (© sandbaseai). 1,318 words, ~2,554 tokens.

Download SKILL.mdSave it as .claude/skills/seo-keyword-insights/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
seo-keyword-insights
description
Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities. Use when asked to discover or prioritize keywords, assess search demand or ranking feasibility, map intent and topics, find competitor gaps, plan organic-search landing pages or content, or analyze a website's SEO opportunities.

SEO Keyword Insights

Build a decision-ready organic-search strategy from a site, product, seed topic, or competitor set. This Skill is a SandBase API workflow: it calls the named SEO capabilities in the SandBase API map through the SandBase MCP gateway. Use an authorized SandBase MCP connection and the discover → inspect → run workflow below; never request, print, or store an API key in the research output.

The primary capability is DataForSEO keyword search through SandBase: discover candidates, validate demand and difficulty, compare site visibility, and inspect live SERPs. Read example workflows when the user needs a starting prompt or wants to understand the output.

Operating principles

  • Start from the business and audience, not a brand-name keyword list.
  • Treat tool-returned metrics and SERP results as evidence; treat model-generated keywords, intent labels, and recommendations as hypotheses or judgment.
  • Select the country, language, device, and search engine deliberately. State any default rather than silently assuming a market.
  • Optimize for qualified organic traffic and the site's conversion model, not volume alone.
  • Inspect live SERPs before recommending a page type or claiming a ranking opportunity.
  • Keep user domains, competitor lists, raw exports, and strategy confidential. Return a summarized report unless raw data is requested.

Workflow

1. Frame the decision

Collect or infer the target site or product, target market, language, conversion goal, audience, content scope, and competitors. Classify the request as one or more of: discovery, site opportunity, competitor gap, content roadmap, or page keyword map.

If a site is supplied, form a compact site brief before researching: category, offer, ICP, jobs-to-be-done, differentiators, conversion action, current content themes, and exclusions. Inspect the homepage and a small set of representative product, use-case, pricing, docs, and content pages. Use a SandBase site/content capability when available; use SandBase web search only as a fallback. Record inaccessible or JavaScript-heavy pages as evidence gaps.

When market details are missing, choose a defensible default only if the site or request makes one clear; otherwise ask for the market. Never merge metrics from different markets or engines without labels.

2. Select and call SandBase capabilities

Read the SandBase API map before selecting tools. Treat each listed tool_name as a capability identifier to resolve through the SandBase gateway:

  1. Use sandbase_discover with the provider and capability to find the current endpoint name.
  2. Pass the returned name to sandbase_inspect; read inputSchema, pricing, and execute_as.
  3. Follow execute_as to call sandbase_run using execute_as.arguments.name and schema-defined arguments. If it returns a run_id, poll sandbase_run_get within the task budget until completed or failed; report pending or failed runs without automatically resubmitting them.
  4. Keep the returned endpoint name, market, language, device, and timestamp with the returned data.

Use the API map to select the intended SEO capability and sandbase_discover to resolve its current name. If it is unavailable, search for a relevant alternative and verify it with sandbase_inspect before running it.

Prefer this evidence ladder:

  1. Site/content parsing for the supplied site.
  2. Keyword discovery from site-derived, product, problem, use-case, and integration seeds.
  3. Demand, difficulty, trend, and clickstream metrics for the shortlisted candidates.
  4. Ranked-keyword, competitor, and intersection data when a domain comparison is useful.
  5. Live organic SERPs for the leading candidates and each priority cluster.

The API map intentionally fixes the product-facing capability names, while sandbase_inspect remains authoritative for payload shape, supported locations, and optional parameters. If an expected capability is unavailable, identify the evidence gap and continue only with evidence that is available.

3. Build and validate the keyword universe

Create 3–10 justified seed themes from the site brief or product description: category, capability, use case, pain point, buyer role, integration, comparison, and transactional or informational modifiers. Keep brand terms separate unless brand SEO is explicitly in scope.

Expand a small number of diverse seeds first, then deduplicate and remove clearly irrelevant, unsafe, navigational, or off-market terms. Preserve the provenance of each candidate: site, seed, suggestion, related, competitor, SERP, or hypothesis.

Validate the promising candidates with the available SandBase capabilities. Keep search volume, difficulty, CPC, trend, clickstream, rank, and SERP features in their original market and source context. Mark unavailable metrics as unavailable; never estimate them.

For competitor work, distinguish:

  • coverage gap: a competitor ranks and the target does not;
  • performance gap: both rank, but the target is materially weaker;
  • strategic gap: the query fits the target's offer but no adequate target page exists.

Do not call every available provider merely because it exists. Stop expanding once clusters have enough evidence to make a decision; expand again only for thin or ambiguous clusters.

Use the keyword capabilities deliberately:

  • Start with keyword_suggestions, keyword_ideas, related_keywords, or Google Ads seed expansion.
  • Use search_volume, historical volume, Google Trends, and bulk difficulty only after shortlisting candidates.
  • Use keywords_for_site and ranked_keywords to distinguish existing coverage from true gaps.
  • Use competitors_domain, domain_intersection, and serp_competitors only for a justified competitor comparison.
  • Use Google organic SERP and related/autocomplete queries to validate intent and the recommended page type.
Show full SKILL.md (503 more words)Show less
4. Interpret intent, competition, and opportunity

Cluster validated candidates by user problem and shared ranking intent, then label each cluster with funnel stage and the best page purpose. Use live SERPs to verify whether the query rewards a product page, feature page, comparison, integration page, programmatic template, documentation, category page, or editorial content.

Score at cluster level before scoring individual keywords. Use a transparent qualitative scorecard:

DimensionQuestion
Qualified demandIs the audience and demand meaningful for the business?
Commercial fitCan the offer or a conversion path serve this query well?
FeasibilityDo difficulty, incumbent quality, topical authority, and SERP shape make entry plausible?
Strategic leverageDoes winning support positioning, product adoption, or a reusable page family?
Evidence confidenceAre the market, metrics, and SERP evidence sufficiently complete?

Explain the reasoning behind each priority. Do not use a universal volume or difficulty cutoff: an opportunity's threshold depends on the market, query intent, business value, and the target's authority. If the user supplies a threshold, honor it and show which candidates meet it.

5. Produce an execution plan

Return a concise report using the report template for full deliverables. Separate observed data, calculated prioritization, and strategic judgment. Include assumptions, market labels, sources/capabilities used, data gaps, and next validation actions.

For every recommended page, specify its target cluster, primary query, supporting queries, intent, proposed page type, angle, conversion path, and SERP evidence. Recommend updates to an existing page when that is stronger than creating a new URL. Flag potential cannibalization between pages targeting the same intent.

Example tasks

  • “Find non-brand keyword opportunities for example.com in the United States. Prioritize commercial intent and show the evidence behind every recommendation.”
  • “Expand AI agent observability into keyword clusters, then validate volume, difficulty, trends, and the Google SERP for the top cluster.”
  • “Compare our-domain.com with competitor-a.com and competitor-b.com. Separate coverage gaps from performance gaps and recommend the next three pages.”
  • “Audit the keywords this domain already ranks for. Identify which existing pages should be improved before creating new content.”
  • “Research keyword opportunities for CRM software in Germany. Keep Germany/German metrics separate from any English-language research.”

Quality gate

Before delivering, verify that:

  • The site brief supports the selected seeds, or a no-site scope is explicit.
  • Every metric is source-backed and labeled with its market or marked unavailable.
  • Intent and page-type claims for priority clusters have live-SERP evidence.
  • Competitor claims distinguish observation from inference.
  • Priorities favor qualified outcomes and feasibility, not a single vanity metric.
  • Recommendations are specific enough to hand to content, product marketing, or SEO owners.

Failure handling

  • If SandBase is unavailable or unauthorized, report the failed capability and ask the user to connect or authorize SandBase; do not silently substitute a direct provider API.
  • If a capability returns incomplete data, keep partial findings, downgrade confidence, and name the missing evidence.
  • If crawling is blocked, analyze accessible pages and clarify that the site brief may be incomplete.
  • If no feasible priority emerges, report that finding and recommend a validation, authority-building, or paid-discovery path rather than inventing an opportunity.

© sandbaseai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in marketing/seo-keyword-insights of sandbaseai/sandbase-skills.

  • SKILL.md
  • references/example-workflows.md
  • references/report-template.md
  • references/sandbase-api-map.md

Open the folder on GitHubat commit cbab581

Compare with similar skills

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Scroll World Landing Pageoso95/scroll-world9.9k1 repos~12kAutomated safety check: NotesMIT
Expert Panelericosiu/ai-marketing-skills3.6k2 repos~2.1kAutomated safety check: PassMIT
UI UX Pro Maxsaoudi-h/solar-icons19018 repos~11kAutomated safety check: NotesCustom licence
Frontend Designanthropics/skills180k38 repos~2.3kAutomated safety check: PassApache-2.0

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Questions about SEO Keyword Insights

What does SEO Keyword Insights do?

Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities. SEO Keyword Insights is an agent skill from sandbaseai/sandbase-skills. Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities.

When should I use SEO Keyword Insights?

SEO Keyword Insights fits situations like: asked to discover; prioritize keywords; assess search demand; ranking feasibility.

How do I install SEO Keyword Insights in Claude Code?

Run `npx skills add sandbaseai/sandbase-skills --skill seo-keyword-insights -a claude-code`. Or copy the skill folder (marketing/seo-keyword-insights in sandbaseai/sandbase-skills) into .claude/skills/seo-keyword-insights in your project. Claude Code loads it when a task matches its description.

How do I install SEO Keyword Insights in Codex?

Run `npx skills add sandbaseai/sandbase-skills --skill seo-keyword-insights -a codex`. Or copy the skill folder (marketing/seo-keyword-insights in sandbaseai/sandbase-skills) into .agents/skills/seo-keyword-insights in your project. Codex loads it when a task matches its description.

Can I use SEO Keyword Insights in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sandbaseai/sandbase-skills --skill seo-keyword-insights -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-keyword-insights, .gemini/skills/seo-keyword-insights, .github/skills/seo-keyword-insights and .opencode/skills/seo-keyword-insights in your project.

What does SEO Keyword Insights need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Keyword Insights is instructions for the agent only.

Does SEO Keyword Insights access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Keyword Insights safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Keyword Insights use?

SEO Keyword Insights is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Keyword Insights use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.5k tokens, read only when the agent opens those files.

What are the alternatives to SEO Keyword Insights?

Skills that share tags, products or a category with SEO Keyword Insights: Impeccable (bestofjs/bestofjs, 3.1k stars), Scroll World Landing Page (oso95/scroll-world, 9.9k stars), Expert Panel (ericosiu/ai-marketing-skills, 3.6k stars) and UI UX Pro Max (saoudi-h/solar-icons, 190 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Keyword Insights?

sandbaseai (a GitHub organization) maintains it in sandbaseai/sandbase-skills, which has 203 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on September 26, 2026.

Source: sandbaseai/sandbase-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.